Everest Group - Reimagining the Enterprise Operations Model...REIMAGINING THE ENTERPRISE OPERATIONS...

w w w . e v e r e s t g r p . c o m

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AN EVEREST GROUP VIEWPOINT

R

This report has been licensed for exclusive use and distribution by TCS

Reimagining the Enterprise Operations Model

Driving a Silo-Breaking, Digital-Native Approach to Operations Transformation

Chirajeet Sengupta, Partner

Rajesh Ranjan, Partner

Skand Bhargava, Practice Director

Mukesh Ranjan, Senior Analyst

Copyright © 2019, Everest Global, Inc. All rights reserved.

http://www.everestgrp.com/

https://www.everestgrp.com/


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REIMAGINING THE ENTERPRISE OPERATIONS MODEL

Introduction

Business models – under the influence of Industry 4.0 disruptions – are rapidly changing

and, consequently, enterprises are pressed to manage these changes in a comprehensive,

integrated manner across IT and business operations.

The fourth generation of the enterprise is characterized by a transition from mechanization

(Gen 1) to mass production (Gen 2) to computerization (Gen 3) to an era characterized by

the seamless infusion of the digital with the physical and the human.

Most enterprises undergoing digital transformation journeys as part of their move to Gen 4

realize only partial success through their initiatives. For an enterprise to be able to scale

digitally, it has to go beyond technology change and transform its operating model as well.

While most enterprises understand and appreciate the need for a technology change, the

corresponding operating model adjustments remain challenging.

Lack of focus on operating model change often leads to a “digital dip” in which companies

experience limited digital success after an initial successful run. Both digital-native

companies and traditional enterprises can get trapped in the digital dip as they are

overly reliant on technology without the necessary operating model changes.

The rewards of a digital-native operations model are significant. 79% of firms that adopt a

digital-native operations model say they are on their way to establishing market leadership

in their respective industries. An equal percentage also believe that they are in a better

EXHIBIT 1

Evolution of the Generation 4

enterprise

Source: Everest Group (2019)

Generation 1Mechanization of industry

Generation 3Computerization

Generation 2Mass production

Generation 4⚫ Physical + Digital integration⚫ Ambient and embedded data

and intelligence⚫ Highly automated




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in a better position to serve new markets and customer segments. Enterprises

leveraging a digital-native operations model have also been able to achieve an average

1.7X cost savings, compared to those that have not initiated similar changes1

The report explains the key questions every enterprise must ask before undertaking

the journey to the Gen 4 digital operating model, including:

1 Everest Group survey with 200 CXOs from large enterprises (more than US$ 1billion in revenues)

What are some of the conditions that determine suitability for such a transformation journey?04

What are the typical operating model changes than an enterprise has to undergo as a part of digital-native transformation?

03

What key benefits can we achieve through digital transformation initiatives geared towards building a Gen 4 enterprise?01

What are the typical technology changes that an enterprise has to undergo as a part of digital-native transformation?

02




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Enterprise value drivers

Everest Group take

The key imperatives driving enterprise success in the digital age include superior customer

experience, faster time-to-market, and continuous innovation in products and services.

However, most enterprises fail to realize the complete benefit from their digital initiatives.

A siloed technology adoption strategy, instead of transforming core operations with the

help of technology, limits digital value capture. The key reason for this limited success is

siloed enterprise operations across IT, Infrastructure Services & Business Process, instead

of an integrated operations focusing on business KPI's and driving transformation aligned

to strategic business priorities

Successful transformation programs rely on changes in organization and operations in

conjunction with technology transformation initiatives:

⚫ ING embarked upon an Agile transformation journey, creating 350 nine-person

squads in “tribes.” The Agile transformation resulted in significant benefits through

improved time-to-market and enhanced customer engagement

⚫ Subway overhauled its entire operations model to create a personalized user

experience at every touchpoint. The most notable reason for Subway’s success was

ensuring that the new model remains dynamic through continuous innovation

“In any business, you need to have a model that makes those big decisions objective.

But just because you build a model, it doesn’t mean it should be static. You should

always change it, always be dynamic and update it.”

– Chad Sanderson, Digital Optimization Lead

⚫ Rolls-Royce accelerated its digital transformation program to speed up the

development of new products and services for its customers. It is leveraging fast-

paced data innovation to improve service and develop new products to improve its

time-to-market by 50%

“Digital transformation has helped us reduce time-to-market and reduce cost. We are

using data to design and make engines better.”

– Ben Story, Strategic Marketing Director

EXHIBIT 2

Key imperatives for

enterprise success in the

digital age



79%of enterprises believe that

faster time-to-market

is a key priority for

digital success1

89%of enterprises believe that

superior customer experience

is a top priority for digital

success1

of digitally mature enterprises

actively invest in continuous

innovation in products and

services versus the industry

average of 31%1

74%




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What does it take to be a digitally successful enterprise?

Everest Group take

Most transformation initiatives can achieve success in sub-scale projects. The challenge lies

in scaling digital success across the breadth and depth of enterprise functions, resulting in

new business models. A scalable digital transformation approach requires enterprises to

make investments along two dimensions - technology and operating model. Enterprises

that are able to transform along both dimensions reap the full benefits of digital

transformation.

Why are enterprises not able to realize success from their digital initiatives?

Most enterprises, in an effort to achieve quick results, equate digital transformation with

either technology implementation or process reengineering. To gain true digital success,

enterprises need to focus on both technology and operating model transformation beyond

process optimization initiatives.

Enterprises that are able to carry out digital transformation with a balanced focus on

operating model changes and technology changes exponentially increase the probability

of achieving digital scale.

EXHIBIT 3

Approach to a successful

digital transformation


Change in technology

Ch

ange

in o

per

atin

g m

od

el

Digital dip

Constrained efficiency Digital scaling

Digital laggards




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Zone of the digital dip

Enterprises that focus extensively on technology transformation without corresponding

changes in the operating model often fall into the digital dip, and are unable to sustain the

initial levels of success realized through technology transformation. The digital dip is caused

when they experience roadblocks impeding success with digital transformation. Ultimately,

most enterprises are unable to surmount this dip, resulting in digital transformation

initiative failure.

EXHIBIT 4

Zone of constrained efficiencies

Enterprises that focus extensively on operating model changes without adequate

investments in technology land in the zone of constrained efficiency. Traditional enterprises

often undertake this approach as part of which they undertake transformation initiatives to

overhaul their complex operating model. However, in the absence of technology

transformation, operating model changes are often limited to superficial restructuring of

business units, and process reengineering initiatives that are focused on driving tactical, and

often incremental efficiencies that lose relevance with a changing business environment,

Digital dip zone


EXHIBIT 5

Constrained efficiencies zone


Digital transformation timeline

Zone of take-off: Enterprises start to implement a digital-native operating model. Only enterprises that are able to surmount the digital dip achieve scalability.

High

Low

Digital dip

Technology transformation

Technology + Operating model transformation

Initial enthusiasm backed by high levels of technology investment

Dig

ital

su

cces

sEf

fici

ency


No transformation

Traditional operations re-engineering

Operating model + technology transformation

Typically 2-3X

Roadblocks typically caused by siloed approach, confusion on KPIs, conflicting stakeholder views, and poor user adoption




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Understanding technology transformation

Everest Group take

Most enterprises take a siloed, fragmented approach to technology implementation,

with sub-optimal results. To drive technology transformation, a comprehensive IT and

operations technology framework leveraging AAAC (agility, analytics, automation, and

cloud) is required to achieve transformation objectives.

A technology transformation model brings together elements of agility, automation,

and analytics in an integrated IT-operations environment to break the siloed nature of

transformation that most enterprises employ. Cloud often forms the bedrock of such a

technology transformation.

EXHIBIT 6

Technology transformation

model


Traditional siloed operations model

Loosely coupled

Infr

astr

uct

ure

Dat

a-ce

nte

r

EUC

Secu

rity

Siloed on-premise Infra towers

Siloed process innovation

Ap

plic

atio

ns

ERP 1 ERP 2

Other legacy apps

….

Reconciliation Workflow

Non-configurable

portals

Data management

Excel macros Basic reporting

Loosely coupled

!

Op

era

tio

ns

Drive stakeholder experience

Drive decisions

Drive process efficiency

Drive scalability and performance

IoT

API ecosystem

Innovation ecosystem

Interactive applicationsVirtual agentsDevicesC

ogn

itiv

e /

Art

ific

ial

Inte

llige

nce

Interaction layer

Enab

lers

Business intelligence Process mining

Insights layer

Analytics

IT applicationsBusiness softwareProcess automation

Automation layer

CloudNetwork & security DevOPs

Cloud-based IT infrastructure

APIsTraditional apps Modern apps

Integrated IT-operations model Objectives




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Transitioning from a traditional business model to a technology transformation model

requires four key changes.

IT stack collapse

In the new model, the traditional siloed IT stack collapses into a pod-type model based on

technology advances such as cloud, software-defined infrastructure, operations

automation, and containers. The infrastructure and application layers bring together the

requisite business and cross-functional talent with the core objective of conceptualizing and

delivering specific business outcomes on a continuous basis.

Clearly defined insights and experience layers

Technology investments in improving customer experience are often fragmented and

limited to innovations in the interaction channel (e.g., chatbots). By defining a clear insights

layer that integrates multiple channels with systems of records and modern apps, the new

operating model ensures recency of “customer memory.” In other words, customers’

unique behavioral identities and preferences are consistently managed across multiple

channels and transactions, eliminating friction. For instance, a retail banking customer’s

preferences across interactions (such as cards and mortgages) are “remembered.”

Incorporation of external data sources

Internal data such as operational data, transactional records, and customer metrics, are

lagging performance indicators and provide insights only on historical events. Today,

enterprises need to monitor and analyze disparate external data sources to build and

maintain a clear and current picture of their environment. By identifying and seamlessly

integrating new, external data sources into the decision-making process, enterprises

identify and integrate insights on forward-looking consumer trends, market demographics,

and competitive developments.

“Companies have become a little more outward-focused because of external data, and use

of this data is changing the way insurers view and interact with the external world.”

– Upendra Belhe, SVP and Chief Enterprise Business Analytics Scientist,

Chubb Group of Insurance Companies

Retail companies such as P&G, HUL, and Amazon buy and deliver customized ads based on

external datasets such as a country’s demographic, consumption, and weather. Banks use

external data to create customized and targeted offerings

EXHIBIT 7

IT stack collapse


Infrastructure

Middleware

Applications

The traditional IT stack

silos

silo

s

The collapsed IT stack

Pu

blic

Paa

S

SaaS Pvt

PaaS

SDI Converged

IaaS




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Smart automation as an enhancer

The automation layer plays a key role in bringing together the combined IT and operations

layers. The automation layer needs to straddle both IT and business process automation in

order to offer a seamless, straight-through experience, as well as to create a feedback loop

that manages the impact of changes in the technology or business environment. “Intelligent

automation” initiatives that combine RPA with advanced cognitive technologies need to be

implemented in ways that take into account both the existing technology landscape as well

as the business process dependencies to drive unified outcomes.




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Understanding operating model transformation

Everest Group take

The journey to a digital-native operations model is a multi-stakeholder conversation at the

board level. It requires significant culture change, initial access to differentiated talent, a

targeted plan to upskill the existing the talent base, and – most importantly – a long-term

commitment to change. Governance is critical, and enterprises need to measure value

through a set of evolving metrics across technology, operational agility, and business

outcomes.

Organization structure

Nearly 70% of enterprises believe organization structure is a barrier to scaling up their

digital initiatives.1

Traditional organizational structures have been characterized by:

⚫ Inside-out definitions: Functions and sub-functions have been built on the enterprises’

focus on driving task efficiency. Over time, this has resulted in a siloed and fragmented

organization that focuses narrowly on efficiency, with little focus on the customer needs

Using the customer journey as the true north, enterprises need to break organizational

silo-s to drive a singular focus on the customer experience

⚫ Siloed shared service structures: Traditional enterprise IT structures have been built

around tower-based models. Similarly, traditional operations structures to support

functions such as procurement, HR, finance typically scale through some form of shared

services. In a traditional model, these structures offer unit cost efficiency and narrow

specialization. But, in a modern enterprise trying to scale a digital operating model,

these structures impede agility and innovation by being siloed from each other and from

core business

The next generation of organizational structures will need to be characterized by:

⚫ Central innovation organizations that serve as governors of the transformation journey

by focusing on the central mandates of risk and compliance, and support pan-enterprise

funding for specific initiatives

⚫ Agile Ninja squads: High-powered, small teams that are tasked with incubating

initiatives across different functions and business units. The core mandate of the Agile

Ninja squads comprise:

– Rapid prototyping and MVP evaluation for specific initiatives

– Sharing and seeding of best practices, knowledge, and expertise

– Eliminating waste and duplication of initiatives

EXHIBIT 8

Operating model

transformation



Talent model CultureFunding GovernanceOrganization

structure




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⚫ Digital command centers that are tasked with adopting and scaling innovation

outcomes. These centers need to be integrated and cross-staffed with personnel across

business operations and technology. Essentially, they are the digitally-integrated

versions of the traditional siloed shared services structures that seamlessly blend

technology into the enterprise run model.

Funding

Approximately 45% of the enterprises fail to implement or sustain their digital initiatives

due to lack of sustainable funding.1

Scaling digital transformation comprises several iterative, multiyear journeys that require

enormous change to reinvent the business and create new value for customers, employees,

and shareholders. Though the overall spend on digital initiatives has increased, most digital

initiatives do not reach scale due to budget constraints. Enterprises generally face one or

more of the following three challenges:

⚫ Business case and ROI: Typical funding models focus on achieving a specific business

case, based on certain assumptions established at the beginning; those assumptions

often turn out to be incorrect

⚫ Budget timing: Most companies plan capital budgets for technology investments every

12 months, which fundamentally go against the agile, rapidly iterative, and adjusting

journey cycles

⚫ Budget allocation: Capital budgets in enterprises are often controlled by a centralized

unit rather than the business units. A scalable digital transformation initiative requires

budget allocation across business and functional units

EXHIBIT 9

Organizing principles for

digital transformation



Central innovation organization

Agile Ninja squads Digital Command Centers

Staffed with CXOs Cross functional teams comprising technologists, business process SMEs, internal consulting and strategy organizations, change management specialists, etc.

Integrated IT and business process teams

Reports to Board of Directors Individual BU leaders on specific initiatives

CIO and COO

Responsible for Conceptualize and Govern⚫ Vision and strategy⚫ Pan-enterprise initiatives

(e.g., M&A)⚫ Security and compliance

Change and Implement⚫ BU-specific technology

implementation⚫ New offering development

and rollout⚫ New BU/geo set-up,

integration, divestment

Run and Optimize⚫ BAU operations⚫ Continuous analytics⚫ Automation and

optimization initiatives




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Cost metrics⚫ Incident response /

resolution time⚫ Number of tickets managed

per FTE per month⚫ Change management

response and resolution / completion time

⚫ Data backup / restore timeliness

⚫ Timely execution of payment requests

⚫ Resource utilization rate

Corollary to the principles for organization structures described above, multi-modal funding

structures are needed to support transformation journeys structured around different

degrees of centralization/decentralization and paces of iteration:

⚫ Central portfolio funding approach: Transformation journeys comprise projects that

need funding across multiple departments or business units. Many of these projects

might lack the ROI to be funded at an individual level. A portfolio funding approach de-

risks these projects and creates a strong ROI at a portfolio level

⚫ Decentralized venture capital approach: This model uses staged gateways that evaluate

MVPs using a fail-fast approach and rapidly adjust funding to prioritize the innovation

funnel

These funding approaches need to co-exist to balance the conflicting mandates of risk and

innovation and to allow the flexibility necessary to adjust funding at different stages of the

digital transformation journey.

Governance

While the initial measures of success can be technology-led (particularly in situations

where significant legacy estates need to be modernized as a precursor to operations

transformation), the KPIs need to rapidly evolve to agility and business outcome metrics.

For instance, measuring reduction in IT downtime will eventually have to be supplemented

with measurements that correlate IT investments with reduction in process cycle times

(agility) and cost improvements (reduction in supply chain waste), revenues (improvement

in fulfillment rates, customer acquisition rates, etc.) , or customer experience (NPS).

EXHIBIT 10

Governance and KPIs


Degree of IT-business alignment

Alig

nm

ent

wit

h b

usi

nes

s o

bje

ctiv

es

Operational metrics⚫ First Contact Resolution (FCR)⚫ % automated incident

resolution⚫ User productivity⚫ IT downtime⚫ Release frequency⚫ Payment processing accuracy

High

Low

Business metrics⚫ CSAT score⚫ NPS⚫ Time to market⚫ Customer churn⚫ Customer acquisition rates⚫ Improvement in fulfilment

rates

HighLimited




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Talent model

Only 20% of enterprises have a digital talent sourcing strategy that crosses the organization

and is well integrated with business units and functions

As enterprises undergo digital transformation, their skill set mix will change significantly.

Interestingly, much of the narrative today rests on the impact of automation on traditional

skills. However, this is a short-sighted view based on the current inventory of skills. As

automation and intelligence scale within the enterprise, business context will become

invaluable and will lead to a dramatic need for cross-functional techno-ops skills.

As a result of the change in the organizational skill set requirement, the talent pyramid

also will evolve as shown below. Not only is automation likely to eliminate routine,

mundane tasks, but it will fundamentally shift service delivery economics from the

unilateral imperative of flattening the pyramid to a diamond-shaped models.

Evolving talent pyramids

EXHIBIT 11

Talent model


Leaders

Thinkers

Doers


De

man

d f

or

hu

man

cap

ital

New role inclusion + Traditional role

expansion

Narrow specialized skills

Cross functional skillsets

Current environment

Period of transition

Digitally evolved environment

Automation impact Context impact




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Culture

A digital-native operations model requires an ownership-driven culture with focus on

experimentation to reduce the fear of change. There are three key components of culture

in this model: leadership buy-in, collaboration and innovation, and iterative improvements.

Leadership buy-in

Transforming operations models at scale requires overcoming significant inertia, resistance

and top-down mandates as well as cross-stakeholder alignment.

55% of enterprises believe that inadequate leadership buy-in cause a digital transformation

initiative to fail.1

The enterprise transformation model in particular often necessitates fundamental

organizational redesign, requiring a board-level conversation. At the same time, bottom-up

cultural resistance to change driven by fears of job irrelevance needs to be addressed

through effective upskilling and reskilling plans.

Collaboration and innovation

Organizations have traditionally operated in silos across IT infrastructure (end-user

compute, data centers, and security), application development & maintenance, and

business operations (F&A, HR, contact centers) and do not communicate with one another.

Each silo focuses on delivering services within its realm of expertise and is bound by rigid

SLAs; therefore, the lack of collaboration is not surprising.

Only 39% of enterprises believe they have a strong focus on building a collaborative and

cooperative culture.1

More than 80% of enterprises do not have a experimentation- and innovation-driven

culture.1

In a digital-native operations model, building a collaborative culture is a critical

differentiator for successfully scaling digital transformation.

Iterative improvements

Transformation journeys are long and require patience; “rip and replace” approaches do

not yield the best outcomes. Enterprises need to have the right policies and procedures in

place to observe and iterate to success, applying a the test-and-learn approach through the

regular infusion of new skills and technologies into the operating environment, and

regularly measuring results.

65% of CXOs believe that an intelligent enterprise needs to have continuous innovation

programs that deliver progressive value through rapid iteration.1





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Approach to implementing a digital-native operations model

Everest Group take

Enterprises can drive the adoption of a digital-native operations model through an

enterprise-level or a function-level transformation. Identifying the right transformation

approach for the enterprise requires the consideration of multiple factors such as business

health, industry disruption, and digital talent availability.

Determining the right transformation approach

Enterprises can adopt a digital-native operations model through two distinct approaches,

enterprise-level transformation or business function transformation. The former is carried

out across the enterprise quickly to completely transform the operating business model and

gain significant differentiation from competitors. In a functional transformation, the

integrated technology + operations model is applied across discrete parts of the

organization (e.g., claims in insurance, or store management in retail) to identify relevant

business cases and then scale up the transformation across the enterprise in phases.

Enterprises should understand the combination of factors noted in Exhibit 9 to determine

the right transformation approach for them.

Interpreting the framework

The decision on whether to take a business-level transformation or a function-level

transformation approach may not be black and white. Enterprises need to consider multiple

factors to identify the best approach. For example, if an enterprise is nearing its asset

refresh cycle and has a high risk appetite, an enterprise-level transformation may be

appropriate. However, if the enterprise lacks the requisite digital talent and has a vast

legacy infrastructure, the enterprise-level transformation model may be challenging.

Enterprises can leverage the framework presented in Exhibit 9 to aid in decision-making.




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EXHIBIT 12

Enterprise- or function-level

adoption framework


Parameter Transformation approach Parameter range definitions

Business health Poor Poor financial results, low shareholder confidence

Excellent Strong financial results, high shareholder confidence

Corporate holding structure changes

Near Planned changes in the corporate holding structure (M&A/divestment) in the next year

Far No foreseeable changes in the corporate holding structure

Industry disruption Low Tech firms / startups have started entering the industry but have not yet created significant impact

High Tech firms / startups are presenting significant competition to traditional enterprises

Change appetite Low Low confidence in the enterprise’s ability to manage the risk associated with significant change

High High confidence in the enterprise’s ability to manage the risk associated with significant change

Digital talent availability

Low The enterprise has limited access to next-generation talent

High The enterprise has developed a significant base of next-generation talent trough hiring, training, acquisitions, etc.

Asset refresh cycle Near Due date is in less than 12 months

Far Due date is more than 2.5 years away

Legacy environment Low Less than 50% of enterprise environment runs on legacy infrastructure and applications

High More than 80% of enterprise environment runs on legacy infrastructure and applications

Low High

Poor Excellent

Near Far

Low High

Low High

Low High

Near Far

Enterprise-level transformation Function-level transformation




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Case study: changing operating models for regulated divestitures

Overview

As enterprises further develop their business models, they evolve through mergers,

acquisitions, and divestment. Life Science major Bayer announced its acquisition of U.S.

agrochemical and agricultural biotechnology company Monsanto in 2016, with the intent of

both extending its portfolio into adjacent areas and leveraging the asset as a platform for

ongoing innovation in agriculture, including Monsanto’s leading role in digital farming

solutions.

In order to obtain regulatory approval for the acquisition of Monsanto, Bayer had to divest some

of its crop science businesses. In doing so, Bayer had to essentially stand up fully functional

operations for each of its divested businesses – many of which were being served by shared

services organizations across the globe – from day one. Failure to meet the divestiture

stipulations would put the acquisition at risk; at the same time, delays would also jeopardize the

transaction by extending beyond the agreement timeframe. Bayer needed to find a way to

successfully divest the necessary business units in a very short timeframe.

Scope

• The businesses Bayer needed to divest spanned 140 sites in 26 countries, and included 4,300

employees and 43 legal entities

• Bayer had to separate all elements of the divested business from the parent organization,

including capital assets, IP, people, processes, and technology. The divested organizations

had to be fully operational and compliant from day one, including all business functions

across core operations as well as corporate functions such as HR, procurement, finance, and

IT

• The IT landscape alone involved more than 400 non-ERP applications, 700 servers, and 4,500

end users spread across 140 sites globally

Transformation approach

Bayer adopted a digital native transformation model as a part of its divestiture approach

• Integrated carveouts: For each divested business, the Bayer team had to carve out business

processes the underlying technology. Given regulatory requirements and the required pace

of change, Bayer would not have succeeded if it had attacked processes and technology

stacks in isolation. Instead, Bayer created a scalable, repeatable carve-out solution spanning

the complete stack of IT systems, infrastructure and operations, to execute the divestiture of

multiple business entities

• Agile and iterative: One of the most critical parts of the entire exercise was identifying the

requirements and the economic impact of new operating models for the divested

businesses. Given the stringent deadlines, Bayer was compelled to act with imperfect

information and was not in a position to build complete and validated baselines upfront.

Consequently, the transition team built the carveout program on assumption-based

economic models that it refined over multiple successive iterations. Bayer defined clear

tollgates and input-output metrics as part of the business planning procedures, updating

output models as it received input information. Output metrics, in turn, determined what

was required for the divested business to be self-sufficient and compliant. Such an agile and

iterative process is typical of transformation programs with dynamic business requirements –

Bayer was able to successfully navigate a complex environment by not creating hardwired

end states




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• Cloud-first approach: Bayer adopted a business-oriented, cloud-first approach to defining

the end-to-end business processes, and set up a cloud-based solution environment for the

vast majority of the divested businesses, including the complete stack of infrastructure, IT

applications and enabling business process services, all of which it transferred to the acquirer

at closing

• Combination of centralized and decentralized decision-making: While a central M&A

organization governed the overall divestiture program, Bayer created embedded project

teams that were responsible for standing up separate businesses. Specific requirements and

characteristics of each business (e.g., local market regulations) influenced decision points for

each divested business

• Technology and process playbooks: Bayer evolved a set of standard process and technology

playbooks to stand up the newly divested businesses (e.g., network procedures, Cloud First

principles, etc.). The new operating models were characterized by lean fit-for-business

processes and standard operating procedures based on the new IT systems and the needs of

a small to medium-sized company. At the same time, several decisions needed to be

customized to suit the specific needs of a divested business. For instance, automation

initiatives were governed by the scale and complexity of the individual businesses – large

complex businesses justified significant investments in automation, while smaller businesses

did not merit the same level of automation investments

Impact

Bayer was able to meet all regulatory requirements and proceed with the Monsanto acquisition.

By codifying the knowledge gained in the form of a carveout factory playbook and a set of

standard operating procedures, Bayer is now on an accelerated path to running similar

initiatives.

Key learnings

The Bayer story is instructive on multiple counts – it highlights the fact that the tenets of a

modern transformation strategy are applicable in situations that are not necessarily driven

exclusively by technology changes. Operating model changes are often triggered by a broader

set of drivers – but there may be relatable pointers from which enterprises can learn. In complex

situations where ambiguous requirements and a need for accelerated change define the

environment (as they did for Bayer), enterprises need to design transformation journeys that

incorporate some of the factors that were instrumental to Bayer’s success, such as:

• Agile and iterative approach: The complex nature of the divestiture meant that an iterative

approach was required to tackle new challenges and come up with a repeatable model

• Governance: The new entities’ need for complete independence required Bayer to set in

place proper policies and procedures. Bayer proactively developed and established these

standards

• Multi-layered projects: Execution of these divestments required multiple cross-skilled teams

to work on projects within projects. These teams maintained strong back-and-forth

communication channels with the core M&A teams

• Transparency and collaboration: Operating in a highly dynamic and complex environment

required multiple teams (local market businesses, central M&A teams, carveout teams, etc.)

to stay well coordinated at all times. Each team realized that it had to invest

disproportionately in ensuring all other teams were updated with current information –

including a common understanding of challenges. By being completely transparent at all

times, Bayer was able to ensure that multiple moving pieces eventually came together to

form stable operations for the divested businesses




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Is the digital-native operations model what your enterprise needs?

The following statements are starting considerations to evaluate the need for a digital-native operations model within an enterprise.

Please determine whether or not you agree with the following statements about your current business environment.

Business considerations

1. Our traditional business model is at risk of disruption by new digital-native competitors

2. We would like to augment our traditional business with digitalized products and services

3. We are considering impending M&A/divestment initiatives

4. We have an aggressive schedule to expand into new geographies and/or business

segments

5. We have an aggressive schedule of rolling out new products and services

6. Our business goes through significant seasonal peaks and valleys

Operating and technology environment considerations

1. Technology modernization is a key priority for us

2. We are planning to migrate, or have already migrated, significant parts of our

applications to the cloud

3. We want to coordinate across decentralized technology adoption initiatives across the

enterprise

4. We believe we can unlock significant business value from a systematic analysis of

enterprise and customer data

5. We believe IT and process automation can not only reduce costs but also be a

competitive advantage for our business

6. We are open to reengineering some of our business processes

Digital maturity considerations

1. Digitalization is a CXO conversation in our organization

2. We believe that digitalization requires a combination of business process reengineering

and technology investments

3. We have a collaborative culture

4. We believe in continuous improvement and innovation cycles rather than Big Bang

projects

5. We need to accelerate implementation in our digitalization programs

6. We are open to augmenting and investing in our existing talent base to succeed in the

digitalization journey

If you answered “yes” to at least three of the questions in each of the three categories, you

are a strong candidate for the digital-native operations model.




2019

EGR-2019-X-V-XXXX

20

About Everest Group

Everest Group is a consulting and research firm focused on strategic IT, business services, and

sourcing. We are trusted advisors to senior executives of leading enterprises, providers, and

investors. Our firm helps clients improve operational and financial performance through a

hands-on process that supports them in making well-informed decisions that deliver high-

impact results and achieve sustained value. Our insight and guidance empower clients to

improve organizational efficiency, effectiveness, agility, and responsiveness. What sets

Everest Group apart is the integration of deep sourcing knowledge, problem-solving skills

and original research. Details and in-depth content are available at www.everestgrp.com.


For more information about Everest Group, please contact:

+1-214-451-3000

[email protected]

For more information about this topic please contact the author(s):

Rajesh Ranjan, Partner

[email protected]

Chirajeet Sengupta, Partner

[email protected]

Skand Bhargava, Practice Director

[email protected]

Mukesh Ranjan, Senior Analyst

[email protected]

This study was funded, in part, by TCS




mailto:[email protected]





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